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Record W2085456640 · doi:10.5195/contemp.2014.96

Culture v. Capital: The Rebecca Belmore Case

2014· article· en· W2085456640 on OpenAlexaboutno aff
India Rael Young

Bibliographic record

VenueContemporaneity Historical Presence in Visual Culture · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsRedressIndigenousArt worldValue (mathematics)LawDeclarationPlaintiffPaintingSociologyIdeologyContemporary artPolitical scienceVisual artsArtArt historyPolitics

Abstract

fetched live from OpenAlex

This paper considers a civil suit between an artist and her former gallery dealer. In the case of Nadimi v. Belmore, the plaintiff and the defendant exemplify two opposing ideologies, which in turn reflect two possibilities for understanding art. This paper considers the case, and Belmore’s artworks as representative of both systems. Through a strategic defense of her art and her practice, Belmore upholds a complex understanding of the value of art. The current legal system, however, only ascribes art value as commodity product. This paper demonstrates how Belmore’s actions and artworks related to the case supersede simple categorization. Her works cannot be corralled into any one classification; they are not only fine art, nor simply First Nations art. The article exposes how her works deploy multiple socio-cultural systems simultaneously: from an Anishnabe worldview, to European-Canadian art history, from the public museum, to the commercial gallery, to the Toronto bound freeway. I contend that this strategic employment of multiple systems is recognized in newly established international law, and articulated in the United Nations Declaration of Indigenous Peoples as traditional knowledge. The Belmore case illustrates the immediate need for governmental systems to acknowledge and employ such international law to redress systemic misconceptions of Indigenous arts practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.429
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.088
GPT teacher head0.276
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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